The present disclosure generally relates to computer-based techniques for ranking autocomplete results. More specifically, the present disclosure relates to a computer-based technique for ranking autocomplete results based on financial-transaction histories of an associated business cohort.
Autocomplete (which is sometimes referred to as word completion) is a widely used technique for predicting a word or phrase that a user wants to type in without requiring that the user completely type the word. In existing autocomplete techniques, the word is predicted based on how similar a typed fragment is to words in a corpus of predefined words (such as a dictionary).
However, the likelihood that a predicted word matches the word the user is typing can vary significantly. For example, certain characters occur more frequently than others in the corpus of predefined words and, in particular, at the beginnings of the words. In addition, the contextual meaning of different words in a phrase can vary considerably depending on the topic. These problems can make it more difficult to correctly predict the word the user is typing and may necessitate the use of longer n-grams to make the prediction, which can degrade the user experience.